AWS Machine Learning Blog

OCTOBER 5, 2023

First, download the Llama 2 model and training datasets and preprocess them using the Llama 2 tokenizer. For detailed guidance of downloading models and the argument of the preprocessing script, refer to Download LlamaV2 dataset and tokenizer. He focuses on developing scalable machine learning algorithms.

Machine Learning 132

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PyImageSearch

SEPTEMBER 23, 2024

Home Table of Contents Deploying a Vision Transformer Deep Learning Model with FastAPI in Python What Is FastAPI? You’ll learn how to structure your project for efficient model serving, implement robust testing strategies with PyTest, and manage dependencies to ensure a smooth deployment process. Testing main.py

Deep Learning 60

Deep Learning Python Computer Vision Software Development 60

Dlabs.ai

JUNE 19, 2020

If you Google ‘ what’s needed for deep learning ,’ you’ll find plenty of advice that says vast swathes of labeled data (say, millions of images with annotated sections) are an absolute must. You may well come away thinking, deep learning is for ‘superhumans only’ — superhumans with supercomputers. Sounds interesting?

Deep Learning 52

Deep Learning Neural Network Machine Learning Computer Vision 52

AWS Machine Learning Blog

JUNE 13, 2023

In this post, we demonstrate how to deploy Falcon for applications like language understanding and automated writing assistance using large model inference deep learning containers on SageMaker. SageMaker large model inference (LMI) deep learning containers (DLCs) can help. amazonaws.com/djl-inference:0.22.1-deepspeed0.8.3-cu118"

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PyImageSearch

JANUARY 1, 2024

pathlib and textwrap are for file and text manipulation, google.generativeai (aliased as genai ) is the main module for AI functionalities, and PIL.Image and urllib.request are for handling and downloading images. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated?

Computer Vision 102

Computer Vision Deep Learning Python Natural Language Processing 102

AWS Machine Learning Blog

JUNE 11, 2024

First, we started by benchmarking our workloads using the readily available Graviton Deep Learning Containers (DLCs) in a standalone environment. In our test environment, we observed 20% throughput improvement and 30% latency reduction across multiple natural language processing models.

Machine Learning 117

Machine Learning Natural Language Processing Software Development ML 117

PyImageSearch

JANUARY 2, 2023

This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research The volume of healthcare-related data is increasing at an exponential rate.

Computer Vision 52

Computer Vision Deep Learning Neural Network Machine Learning 52

Flipboard

JULY 10, 2023

Figure 5: Architecture of Convolutional Autoencoder for Image Segmentation (source: Bandyopadhyay, “Autoencoders in Deep Learning: Tutorial & Use Cases [2023],” V7Labs , 2023 ). time series or natural language processing tasks). This architecture is well-suited for handling sequential data (e.g.,

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AWS Machine Learning Blog

NOVEMBER 27, 2023

of Large Model Inference (LMI) Deep Learning Containers (DLCs) and adds support for NVIDIA’s TensorRT-LLM Library. This file contains the required configurations for the Deep Java Library (DJL) model server to download and host the model. The task parameter is used to define the natural language processing (NLP) task.

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Towards AI

AUGUST 28, 2023

Apply these concepts to solve real-world industry problems in deep learning Taking a step away from classical machine learning (ML), embeddings are at the core of most deep learning (DL) use cases. You can download the images here [4]. You can download the data here (product images by [5]).

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AWS Machine Learning Blog

MAY 1, 2024

AWS Trainium instances for training workloads SageMaker ml.trn1 and ml.trn1n instances, powered by Trainium accelerators, are purpose-built for high-performance deep learning training and offer up to 50% cost-to-train savings over comparable training optimized Amazon Elastic Compute Cloud (Amazon EC2) instances.

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AWS Machine Learning Blog

APRIL 1, 2024

In this blog post, AWS collaborates with Meta’s PyTorch team to discuss how to use the PyTorch FSDP library to achieve linear scaling of deep learning models on AWS seamlessly using Amazon EKS and AWS Deep Learning Containers (DLCs). Alex Iankoulski is a Principal Solutions Architect, Self-managed Machine Learning at AWS.

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AWS Machine Learning Blog

JULY 2, 2024

the optimizations are available in torch Python wheels and AWS Graviton PyTorch deep learning container (DLC). Starting with PyTorch 2.3.1, Please see the Running an inference section that follows for the instructions on installation, runtime configuration, and how to run the tests.

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AWS Machine Learning Blog

MAY 4, 2023

You can use ml.trn1 and ml.inf2 compatible AWS Deep Learning Containers (DLCs) for PyTorch, TensorFlow, Hugging Face, and large model inference (LMI) to easily get started. For the full list with versions, see Available Deep Learning Containers Images. petaflops of FP16/BF16 compute power.

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AWS Machine Learning Blog

OCTOBER 6, 2023

Background of multimodality models Machine learning (ML) models have achieved significant advancements in fields like natural language processing (NLP) and computer vision, where models can exhibit human-like performance in analyzing and generating content from a single source of data.

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Generative AI Prompt Engineer Prompt Engineering Computer Vision 132

Viso.ai

NOVEMBER 19, 2023

This includes various products related to different aspects of AI, including but not limited to tools and platforms for deep learning, computer vision, natural language processing, machine learning, cloud computing, and edge AI. solution architect to learn more about the platform.

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AWS Machine Learning Blog

OCTOBER 19, 2023

Customers increasingly want to use deep learning approaches such as large language models (LLMs) to automate the extraction of data and insights. For many industries, data that is useful for machine learning (ML) may contain personally identifiable information (PII). Download the SageMaker Data Wrangler flow.

Machine Learning 125

Machine Learning Python ML Automation 125

AWS Machine Learning Blog

JUNE 6, 2023

PyTorch is a machine learning (ML) framework that is widely used by AWS customers for a variety of applications, such as computer vision, natural language processing, content creation, and more. These are basically big models based on deep learning techniques that are trained with hundreds of billions of parameters.

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Towards AI

JUNE 27, 2023

For instance, today’s machine learning tools are pushing the boundaries of natural language processing, allowing AI to comprehend complex patterns and languages. However, the rapid evolution of these machine learning tools also presents a challenge for developers.

Machine Learning 98

Machine Learning ML Neural Network Natural Language Processing 98

Viso.ai

DECEMBER 1, 2023

AI vs. Machine Learning vs. Deep Learning First, it is important to gain a clear understanding of the basic concepts of artificial intelligence types. We often find the terms Artificial Intelligence and Machine Learning or Deep Learning being used interchangeably. Get the Whitepaper or a Demo.

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ODSC - Open Data Science

APRIL 3, 2023

Question Answering is the task in Natural Language Processing that involves answering questions posed in natural language. candidate in Machine Learning & Natural Language Processing at UKP Lab in TU Darmstadt, supervised by Prof. Don’t worry, you’re not alone! Iryna Gurevych.

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Neural Network Natural Language Processing NLP Computational Linguistics 117

AWS Machine Learning Blog

APRIL 25, 2024

AWS and Hugging Face have a partnership that allows a seamless integration through SageMaker with a set of AWS Deep Learning Containers (DLCs) for training and inference in PyTorch or TensorFlow, and Hugging Face estimators and predictors for the SageMaker Python SDK. and requirements.txt files and save it as model.tar.gz : !

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AWS Machine Learning Blog

MAY 31, 2023

PyTorch is a machine learning (ML) framework based on the Torch library, used for applications such as computer vision and natural language processing. For a list of NVIDIA Triton Deep Learning Containers (DLCs) supported by SageMaker inference, refer to Available Deep Learning Containers Images.

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ML Auto-classification Auto-complete Natural Language Processing 121

AWS Machine Learning Blog

MAY 31, 2024

Genomic language models Genomic language models represent a new approach in the field of genomics, offering a way to understand the language of DNA. SageMaker notably supports popular deep learning frameworks, including PyTorch, which is integral to the solutions provided here.

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Machine Learning Metadata Large Language Models ML 120

AWS Machine Learning Blog

NOVEMBER 14, 2023

Each works through a different way to handle LoRA fine-tuned models as illustrated in the following diagram: First, we download the pre-trained Llama2 model with 7 billion parameters using SageMaker Studio Notebooks. They can also use SageMaker Experiments to download the created charts and share the model evaluation with their stakeholders.

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AWS Machine Learning Blog

APRIL 19, 2023

The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. With the DJL, integrating this deep learning is simple. Business requirements We are the US squad of the Sportradar AI department. The architecture of DJL is engine agnostic.

ML 95

ML Deep Learning Python Auto-classification 95

Viso.ai

DECEMBER 10, 2023

Image recognition with deep learning is a key application of AI vision and is used to power a wide range of real-world use cases today. I n past years, machine learning, in particular deep learning technology , has achieved big successes in many computer vision and image understanding tasks.

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AWS Machine Learning Blog

JUNE 9, 2023

ONNX ( Open Neural Network Exchange ) is an open-source standard for representing deep learning models widely supported by many providers. ONNX provides tools for optimizing and quantizing models to reduce the memory and compute needed to run machine learning (ML) models. For more details, refer to CreateEndpointConfig.

ML 126

ML Computer Vision NLP Deep Learning 126

ODSC - Open Data Science

JUNE 29, 2023

Let’s download the dataframe with: import pandas as pd df_target = pd.read_parquet("[link] /Listings/airbnb_listings_target.parquet") Let’s simulate a scenario where we want to assert the quality of a batch of production data. The used dataset was adapted from the inside Airbnb project.

Natural Language Processing 104

Natural Language Processing Data Science Data Quality Data Scientist 104

AWS Machine Learning Blog

NOVEMBER 10, 2023

In the recent past, using machine learning (ML) to make predictions, especially for data in the form of text and images, required extensive ML knowledge for creating and tuning of deep learning models. Today, ML has become more accessible to any user who wants to use ML models to generate business value.

Machine Learning 128

Machine Learning Computer Vision ML NLP 128

AWS Machine Learning Blog

OCTOBER 30, 2024

Complete the following steps: Download the CloudFormation template and deploy it in the source Region ( us-east-1 ). Download the CloudFormation template to deploy a sample Lambda and CloudWatch log group. He focuses on building systems and tooling for scalable distributed deep learning training and real-time inference.

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Towards AI

FEBRUARY 13, 2023

A practical guide on how to perform NLP tasks with Hugging Face Pipelines Image by Canva With the libraries developed recently, it has become easier to perform deep learning analysis. Hugging Face is a platform that provides pre-trained language models for NLP tasks such as text classification, sentiment analysis, and more.

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Auto-classification NLP Auto-complete Computer Vision 98

Pickl AI

OCTOBER 16, 2024

Summary: TensorFlow is an open-source Deep Learning framework that facilitates creating and deploying Machine Learning models. Introduction TensorFlow supports various platforms and programming languages , making it a popular choice for developers. It’s an open-source Deep Learning framework developed by Google.

Neural Network 52

Neural Network Deep Learning Machine Learning Natural Language Processing 52

AWS Machine Learning Blog

JUNE 12, 2023

Transformer neural networks A transformer neural network is a popular deep learning architecture to solve sequence-to-sequence tasks. It uses attention as the learning mechanism to achieve close to human-level performance. He helps customers train, optimize, and deploy deep learning models.

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AWS Machine Learning Blog

MAY 13, 2024

Evaluating LLMs is an undervalued part of the machine learning (ML) pipeline. We benchmark the results with a metric used for evaluating summarization tasks in the field of natural language processing (NLP) called Recall-Oriented Understudy for Gisting Evaluation (ROUGE).

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AWS Machine Learning Blog

MAY 30, 2023

For CSV, we still recommend splitting up large files into smaller ones to reduce data download time and enable quicker reads. The single-GPU training path still has some advantage in downloading and reading only part of the data in each instance, and therefore low data download time. However, it’s not a requirement.

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AWS Machine Learning Blog

DECEMBER 6, 2023

Download the Amazon SageMaker FAQs When performing the search, look for Answers only, so you can drop the Question column. He focuses on developing scalable machine learning algorithms. Xin Huang is a Senior Applied Scientist for Amazon SageMaker JumpStart and Amazon SageMaker built-in algorithms.

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